RT Journal Article
SR Electronic
T1 Evaluation of polygenic risk scores for ovarian cancer risk prediction in a prospective cohort study
JF Journal of Medical Genetics
JO J Med Genet
FD BMJ Publishing Group Ltd
SP jmedgenet-2018-105313
DO 10.1136/jmedgenet-2018-105313
A1 Xin Yang
A1 Goska Leslie
A1 Aleksandra Gentry-Maharaj
A1 Andy Ryan
A1 Maria Intermaggio
A1 Andrew Lee
A1 Jatinderpal K Kalsi
A1 Jonathan Tyrer
A1 Faiza Gaba
A1 Ranjit Manchanda
A1 Paul D P Pharoah
A1 Simon A Gayther
A1 Susan J Ramus
A1 Ian Jacobs
A1 Usha Menon
A1 Antonis C Antoniou
YR 2018
UL http://jmg.bmj.com/content/early/2018/05/05/jmedgenet-2018-105313.abstract
AB Background Genome-wide association studies have identified >30 common SNPs associated with epithelial ovarian cancer (EOC). We evaluated the combined effects of EOC susceptibility SNPs on predicting EOC risk in an independent prospective cohort study.Methods We genotyped ovarian cancer susceptibility single nucleotide polymorphisms (SNPs) in a nested case–control study (750 cases and 1428 controls) from the UK Collaborative Trial of Ovarian Cancer Screening trial. Polygenic risk scores (PRSs) were constructed and their associations with EOC risk were evaluated using logistic regression. The absolute risk of developing ovarian cancer by PRS percentiles was calculated.Results The association between serous PRS and serous EOC (OR 1.43, 95% CI 1.29 to 1.58, p=1.3×10–11) was stronger than the association between overall PRS and overall EOC risk (OR 1.32, 95% CI 1.21 to 1.45, p=5.4×10–10). Women in the top fifth percentile of the PRS had a 3.4-fold increased EOC risk compared with women in the bottom 5% of the PRS, with the absolute EOC risk by age 80 being 2.9% and 0.9%, respectively, for the two groups of women in the population.Conclusion PRSs can be used to predict future risk of developing ovarian cancer for women in the general population. Incorporation of PRSs into risk prediction models for EOC could inform clinical decision-making and health management.